Derives an exact formula for the expected reconstruction error energy in compressive sensing under quantization of measurements with arbitrary bit precision, incorporating both quantization noise and approximate sparsity.
On the Errors in Randomly Sampled Nonsparse Signals Reconstructed with a Sparsity Assumption
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Environment-map-aware joint user-pairing and power-allocation improves sum rate and fairness in pinching-antenna EDMA-NOMA systems per simulations against an ablation baseline.
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Quantization in Compressive Sensing: A Signal Processing Approach
Derives an exact formula for the expected reconstruction error energy in compressive sensing under quantization of measurements with arbitrary bit precision, incorporating both quantization noise and approximate sparsity.